WHAT'S HOT?

23 answers about compensation analytics and the ROI of turnover

Oct 04, 2013

Mykkah Herner, M.A., CCP, PayScale

PayScale recently hosted a wildly popular webinar entitled Compensation Analytics: The ROI of Turnover, presented by me, Mykkah Herner. If you missed the webinar, you are welcome to view the slides from the presentation. Since this is a topic of interest to so many of our Compensation Today readers, we're posting my answers to many of the questions received after this webinar here.

Q: Could you use 75% versus 50% to free up your exec to pay as much as needed?

A: Assuming that this question is talking about paying at a particular percentile of the market, organizations can absolutely target the 75th percentile. The decision to pay at the 50th percentile is made when an organization has a strong driving desire to pay at market, or to meet the market, either for philosophical reasons or budgetary ones. Organizations aiming to exceed the market, in order to maintain a competitive edge in attracting and maintaining top talent, will often target anything from the 55th to 90th percentiles. Increasingly organizations are getting specific about which positions they want to target higher (critical skills, managers, directors, etc), and then paying the rest of the workforce at the 50th or 55th percentiles.

Q: could some long term employee turnover indicate that the company does not have a clear explanation of a growth path if applicable? I find we do not communicate a future path for our employees

A: Absolutely. Long term employee turnover can come about due to a number of reasons: lack of adequate career pathing; lack of good manager training; a major shift in the organization’s philosophy, strategy, culture; lack of appropriate incentive to stay; and lack of appropriate pay for appropriate work. In this last case, often organizations will bring employees in at current market rates without checking that existing employees are compensated at a sufficiently higher level based on tenure, experience, and performance (pay compression).

Q: Program management needs a pay cut to pay the engineers at market. What do we do about that?A: While this is said perhaps tongue in cheek, I’d say yes! Exactly. Organizations typically have a finite amount of resources to go around, so the leadership has to get specific about how they want to spend the limited compensation budget. They need to get real about what they want to reward (skills, certain levels, performance, etc), and develop a comp plan around it.

Q: What about the difference between average and median, like in bus dev?

A: Average is the result of adding up a range of values (in this case 5 numbers) and dividing by the total number of values (again 5). Median is the middle number (or the 3rd number in order, in this example). What we see in the example below is that the average falls much higher than the median, implying that there is probably one extreme outlier falling very high above the range – this brings the average up. At the same time, more of the values fall on the lower end, which makes the middle number (median) fall much lower than the average. More incumbents are paid lower, there is one extremely high outlier.

Q: How old is too old for salary data and how do you normalize it to make it more accurate, i.e. robust, to present day?

A: The benefit of working with PayScale is that the data is always current. We add new data points on a daily basis. I never have to worry about old salary data or playing the “age the data” game in excel. The other answer is that the market is very volatile right now. Things are shifting pretty quickly as we start to edge out of the recession in some areas but lag in others.

In this example, we see that the Design Engineer has changed 9.5% in the past year. I’d say using data that was a year old, in this case, would have pretty dramatic effects on retention & attraction of top talent in the position.

Q: How do you deal with promotions where the incumbent is 26% below the starting range for the position? How do we balance this in a time when double-digit increases are not approved?

A: I would start at the policy level. What does your policy say about increase amounts? Is your policy different for increases in conjunction with promotions? In this case, double-digit increases might be absolutely appropriate (in the 10-12ish range). For someone who is greater than 10% below range, I would develop a multi-year plan to bring them up within range. Also, be sure to clarify to the incumbent that you’re doing both a market- and merit-based adjustment. As someone who has been on the receiving end of a market-based increase, without the proper communication, it’s not fun to get to the next increase and receive a “normal” increase. I found myself wondering what I did wrong to get a 3% increase when last time I got 7! As always, communication is key.

Q: How do you handle getting buy-in from the execs for not only a performance review but the comp analysis as well? This is a major hurdle.

A: Comp is a huge part of the bottom line in any organization, sometimes up to 50% of the budget goes to paying salary, benefits, and salary-related fees. It’s critical to not just have a solid performance plan and a strategic comp plan, but to tie the two together. That’s the assurance the organization has, and therefore your execs get, that you’re spending the comp budget in the best way possible. Those who contribute the most to the organization (stellar performance) should get a disproportionately larger piece of the pie.

Q: I must have missed a critial point. If range is how you value jobs, why would you have so many people green circled?

A: I think this is exactly the point. When I start projects with organizations, I am able to show them the current state of where they’re showing up relative to the external market and their internal comp philosophy (ie the ranges). Often what we find at the end of setting up the comp plan is that there are a lot of green-circled employees. This means they aren’t currently paying out their money according to their own comp philosophy. Typically we then work with clients to develop a plan to bring people within range over the course of a year or a few years, depending on the total dollar amount we’re talking about.

Q: Is there a rule of thumb for number of grades?

A: Yes and no. The ideal number of grades will differ by organization depending on a few factors:

How far is it between the lowest and highest paid incumbent in the organization

Are there a lot of leveled positions (Machine Operator I, Machine Operator II, Machine Operator III, etc)? If so, you may need more grades to accommodate the multiple levels and the grades will likely be closer together.

How hierarchical is the structure? Does the company culture support a more flat grade structure or a more vertical one? It should be noted that a comp structure doesn’t necessarily mirror the org structure. Some job skill-sets have a higher value in the market than others; for example, an IT Manager may be at the same organizational level as an HR Manager, but the skill-sets required for the IT job typically place the pay higher than an HR Manager.

Q: With regard to the 3,6, 9 month changes in the Hot Jobs Analysis slide, do you get these amount by market pricing every 3 months?A: The answer will depend on your source of data. Because PayScale adds new data points every day, we are able to get a trend analysis for each job on a quarterly basis. Most traditional sources gather data only every 1-2 years, making a quarterly analysis impossible.

Q: Is the result of the quickpoll about which analytics people intend to use being shared today?A:

I intend to Use this Analytic:

Market Ratio

139

37.98%

Compa-Ratio

118

32.24%

Range Penetration

51

13.93%

Disparate Pay

35

9.56%

Mid to Market Delta

22

6.01%

Compa-Ratio, Market Ratio

1

0.27%

Grand Total

366

100.00%

Q: I am interested in how other companies opt to use which analytic.

A: Great question. In addition to the quickpoll results, which gives us a sense of which analytics folks are intending to use, I’d encourage more open dialogue amongst HR and Comp folks about what it is they use to follow up on their comp plans. What I tend to hear supports the data above, which is that people tend to use Compa-ratios and Market-ratios most often. PayScale hosts a discussion group on LinkedIn for Compensation and Human Resource professionals where you can have these types of open conversations with peers.

Q: Hi, could you please elaborate a bit more on EE Pay distribution?

A: The chart below shows an example of employee pay distribution. It tells you how the employees are spread out across the range to which they’re assigned. In this example, 28 employees fall below range, and 18 fall above range. Then the range itself is broken into thirds with 39 falling in the bottom third, 47 in the middle third, and 29 in the top third of the range.

Besides the obvious (whether someone is low or high), range distributions can tell us some interesting things about how we’re paying people in a certain position. If you have a lot of folks in green *and* a lot of people in red, you may have multiple levels of the same job. Perhaps split the job in two and assign the incumbents to the appropriate level based on skill set, performance, tenure, etc (not necessarily based on pay practices).

Also, if there is a wide distance between the lowest and highest paid incumbent, it merits looking at who falls where along the range. This can be a flag that there are some discrimination issues present.

Q: Would you calculate turnover costs for both voluntary and involuntary terms, or just focus on the voluntary terms?

A: It would depend on the context and what I’m trying to show. The physical costs of turnover for involuntary vs voluntary turnover might differ. If the involuntary turnover is due to performance, disinterest, etc, it’s possible that there was a high cost of error, opportunity cost. So that might actually balance out some of the other tangible costs of turnover.

The more intangible costs would also differ. Sometimes losing someone due to involuntary turnover is a boost to morale in cases of poor performance, poor attitude, etc. Sometimes a voluntary turnover is a morale-killer in cases where the incumbent is a top performer or well-liked in the organization. Lots of variables to consider and ripple-effect of both voluntary and involuntary turnover.

Again, it’ll depend on why you’re calculating the costs. Are you trying to show the amount of work it costs HR to replace people? Or are you doing a more holistic analysis of cost to the organization?

Q: What is the normal range of compa-ratio that an employee should be at?

A: There are really two ways of answering this question. The short answer is that typically folks should fall within 0.8 and 1.2 compa-ratio. The long answer is that it will depend on how wide your range widths are. At entry level positions, with a narrower range width, it’s possible to be above 0.8 compa-ratio but still below the bottom of the range. In Director-level positions, with a broader range width, it’s possilbe to be above a 1.2 but still within range. Ultimately, at the employee level I think it’s more helpful to use the range-penetration measure. At the team or organizational level, compa-ratio becomes more meaningful.

Q: what would be the rationale for changing the spread between the grades? Why wouldn't you want consistency?

A: Consistency can be created in a couple of different ways when creating ranges. I’ve seen a lot of organizations use the same range width and midpoint differential across the full structure. The disadvantage here is that you may have too broad a range for entry-level jobs, which would then make overpaying and underpaying harder to identify. Also, at the top end of the structure, your ranges may be too narrow, creating a false ceiling.

You can also create consistency by using a mathematically sound increase from grade to grade or for range spreads. In the example below, the midpoint differential is constant at 12.5%, but the range width increases by 2 every time.

Q: How to caliculate avg Market percentile of EE base

A: Market Percentiles are actually very complex to calculate. Essentially, you’re calculating the exact point that the employee pay falls along a range of values. In order to do that, you’d have to know the range of values. PayScale’s system is able to calculate this for you behind the scenes.

Q: What if there is no data at P50 ? Would you use Average ?

A: I probably wouldn’t because I wouldn’t necessarily know how skewed left or right the average was. The median data (P50) is typically referred to as “market.” While the average can give you some sense of pay, it doesn’t necessarily tell you where you’re hitting the market. For example, in the above data, the average was around $97K, but the P50 was $80K. That’s a pretty big difference! I’d use internal alignment to help me place this position relative to other positions in the organization.

Q: Non-profit organization may not have a market data. So how do we anlayze the parity within?

A: Increasingly non-profits do have and share market data. PayScale actually has pretty great non-profit data and I’ve worked with a number of non-profit clients will agree with that assessment. In a tight economy where donors have to really pick and choose where they spend their money, non-profits have to get increasingly savvy in demonstrating good stewardship of resources, including solid pay practices. Part of having solid pay practices is having good market data and a fair plan internally as well; part of what donors also like to see is the good ROI of comp budgets as demonstrated through pay for performance which I’m also seeing become more frequent in non-profit arenas. I’d encourage digging deeper for market data as a guide, and then make adjustments to the structure as necessary based on what you know of the positions.

Q: So, am I understanding this correctly? Market-ratio is our comp compared to others in same industry/location and Compa-ratio is what we are paying in comparison to our compensation plan?

A: Yes! You’ve got it! I find that hearing the same terms defined in our own words really helps with comprehension, so I’d encourage everyone to define all these comp terms on your own. That will also help you make sure you can explain it to folks in your organization, from managers to execs.

Q: What is a generally acceptable pay spread percentage?

A: It would probably depend on the level of the position. I would use the range spread as a guide for what’s an appropriate pay spread between incumbents. Entry-level positions I’d expect to see less differentiation (28-40ish%), while at higher levels I’d imagine seeing greater differentiation in pay (up to 60-70%).

Q: How do you determine 'hot jobs'?

A: I’d say this is something you can determine internally for your organization. These are typically the jobs without which you could not get the core work of your business done. In other organizations, these are jobs that have skill-sets that are critical or challenging to find. Another way of finding a hot job is to see who’s asking for more money and leaving for more money in your organization. Sometimes the jobs that turn quickly are also the hot jobs. Hopefully not, as that means you’re paying appropriately and keeping up with the market!

Q: What about salary/pay bands? Who should use them?

A: If we’re talking about pay ranges (typically with a width of 30-60%ish), I’d say all organizations can benefit from having a range for each position to give them a sense of the market value for the job. Additionally, most organizations can benefit from having grades and ranges (structure). I’ve built structures for organizations with as few as 19 people and up from there into the 10s of thousands.

If we’re talking about true pay bands – huge bands of 100-300% width – I’d say that they’re increasingly a thing of the past. It’s hard to really dial in on the pay with widths that big and companies need more control over their payroll dollars in this uncertain economy. Also, it’s hard to use bands to ensure things like lack of discrimination and pay equity.

Thanks to everyone who attended the webinar and submitted questions. In my ideal world, I could facilitate a dialogue amongst folks wanting to understand and use analytics more. I think the more we talk about the numbers behind our hunches, the more they make sense and help us target the critical areas for improvement.